MUMBAI, India, Sept. 14 -- Intellectual Property India has published a patent application (202641105909 A) filed by Dr. A. Priya; Anil Kumar; Tanikella Venkata Suryanarayana Divakar; Dr. Dinesh V. Kala; Dr. Nilesh Bhanudas Raut; Y. R. Dhumal; Dr. V. Susan Jayaseeli Manuel; Dr. Angelin S. Kiruba; Dr. Sandeep Kumar Das; Mr. Pranendu Manna; Dr. D. Helen; and Dr. Namrata Tripathi on September 02, 2026, for Artificial Intelligence–enabled Solar Energy Optimization And Management System.
Inventors include Dr. A. Priya; Anil Kumar; Tanikella Venkata Suryanarayana Divakar; Dr. Dinesh V. Kala; Dr. Nilesh Bhanudas Raut; Y. R. Dhumal; Dr. V. Susan Jayaseeli Manuel; Dr. Angelin S. Kiruba; Dr. Sandeep Kumar Das; Mr. Pranendu Manna; Dr. D. Helen; and Dr. Namrata Tripathi.
The application for the patent was published on September 11, 2026, under issue no. 37/2026.
Abstract: The present invention relates to an Artificial Intelligence–Enabled Solar Energy Optimization and Management System for intelligent monitoring, prediction, optimization, and utilization of solar-generated electrical energy. The system comprises a solar photovoltaic generation unit, sensing and data acquisition unit, data processing module, artificial intelligence module, power optimization module, energy storage unit, battery management module, intelligent energy distribution module, and monitoring interface. The sensing unit continuously acquires parameters including solar irradiance, ambient temperature, photovoltaic panel temperature, voltage, current, generated power, battery state of charge, and electrical load demand. The acquired data is processed and supplied to the artificial intelligence module for analyzing historical and real-time operating conditions and predicting solar power availability and energy demand. Based on the prediction results, the optimization module determines suitable photovoltaic operating conditions and energy utilization strategies. The battery management module dynamically regulates charging and discharging operations according to available solar power, predicted energy generation, load requirements, and battery condition. The intelligent energy distribution module coordinates the supply of electrical energy among connected loads, battery storage, and a utility grid, where applicable. The system further incorporates anomaly detection and performance monitoring for identifying deviations, abnormal operating conditions, and potential performance degradation. Continuous feedback enables adaptive modification of control and scheduling decisions according to changing environmental and electrical conditions. The invention improves solar energy harvesting, storage utilization, energy distribution, and operational reliability while reducing energy wastage and unnecessary grid dependence. The system is applicable to residential, commercial, agricultural, industrial, microgrid, and other renewable energy management applications.
Disclaimer: Curated by HT Syndication.
